We train SSIS-Track by following the training strategies of CondInst [1]} and AdelaiDet [2]}.
For images, we adopt the weights of CondInst trained on COCO [3]} to initialize the weights
of the backbone network, and then use the same parameters in SSIS [4]}, [5]} to train SSIS-Track on the SOBA dataset [6]}.
For videos, we adopt the weights of SSIS-Track trained on images to initialize the the
model, set the mini-batch size as four, and optimize SSIS-Track on an NVIDIA RTX 3090 GPU for 5,000 iterations.
We set the initial learning rate as \(1e-5\)  and reduce it to \(1e-6\)  at 4,500 iterations.
Also, we re-scale the input images without changing the aspect ratio, such that the shorter side is no less than 672 pixels.
